Petri Vuori

Mobile station with audio signal adaptation to hearing characteristics of the user

A method and apparatus for increasing the intelligibility of speech signals received by mobile stations via adapting some of the acoustic parameters of speech in the frequency domain. The mobile station may have the capability to modify speech signal parameters to conform the speech signal to a listeners hearing profile. In an alternative embodiment, mobile station processing and battery power are conserved by the communication network having the capability to modify speech signal parameters to conform the speech signal to a listeners hearing profile. To conserve mobile station memory, the users hearing profile may be stored on the network.

Keystroke recognition for virtual keyboard

The progress in the field of human-computer interaction with hand held electronic devices, such as, personal digital assistants (PDAs) and mobile phones searches for new interaction techniques. Proximity sensing extends the concept of computer-human interaction beyond actual physical contact with a device. In this paper, a virtual keyboard implementation is presented and keystroke recognition experiments with the keyboard utilizing proximity measurements are described. An infrared (IR) transceiver array is used for detecting the proximity of a finger. Keystroke recognition accuracy is examined with k-nearest neighbor (k-NN) classifier while a multilayer perceptron (MLP) classifier is designed for online implementation. Experiments and results of keystroke classification are presented for both classifiers. The recognition accuracy, which is between 78% and 99% for k-NN classifier and between 69% and 96% for MLP classifier, depends mainly on the location of a specific key on the keyboard area.